I am having a lot of trouble trying to implement this on my own, so if anyone can point to, or describe an algorithm I'd be much obliged.
The problem statement
Given one dimensional flattened pointer int* i which would look something like this {1,2,3,4}, and given a list of dimensions in form of a list {2,2} reshape the 1D array to conform with specified dimensions. Overall after the procedure the array should look like {{1,2},{3,4}}.
I am basically asking if anyone knows the algorithm that is used in numpy.reshape.
A n-dimensional array in c is nothing more than syntactic sugar for computing the offset inside a simple array, they look the same in memory (one contiguous block). Therefore, there's really no point in "reshaping" it, as this little sample demonstrates:
#include <stdio.h>
int data[] = {1,2,3,4};
int main(void)
{
int *i = data;
for (int n = 0; n < 4; ++n)
{
printf("i[%d] = %d\n", n, i[n]);
}
int (*j)[2] = (void *)i;
for (int n1 = 0; n1 < 2; ++n1)
{
for (int n2 = 0; n2 < 2; ++n2)
{
printf("j[%d][%d] = %d\n", n1, n2, j[n1][n2]);
}
}
return 0;
}
output:
i[0] = 1
i[1] = 2
i[2] = 3
i[3] = 4
j[0][0] = 1
j[0][1] = 2
j[1][0] = 3
j[1][1] = 4
NumPy doesn't need an algorithm, because it stores data contiguously regardless of the shape. The "shape" property is the only difference between the input and the output of reshape(). The algorithms come into play when later accessing the array, such as when printing it. Then you need to follow the shape to know how many elements go in each row or other dimension.
Related
I'm implementing K Nearest Neighbor in C and I've gotten to the point where I've computed a distance matrix of every point in my to-be-labeled set of size m to every point in my already-labeled set of size n. The format of this matrix is
[[dist_0,0 ... dist_0,n-1]
.
.
.
[dist_m-1,0 ... dist_m-1,n-1]]
Next, I need to find the k smallest distances in each row so I can use the column indices to access the labels of those points and then compute the label for the point the row index is referring to. The latter part is trivial but computing the indices of the k smallest distances has me stumped. Python has easy ways to do something like this but the bare bones nature of C has gotten me a bit frustrated. I'd appreciate some pointers (no pun intended) on what to go about doing and any helpful functions C might have to help.
Without knowing k, and assuming that it can be variable, the simplest way to do this would be to:
Organize each element in a structure which holds the original column index.
Sort each row of the matrix in ascending order and take the first k elements of that row.
struct item {
unsigned value;
size_t index;
};
int compare_items(void *a, void *b) {
struct item *item_a = a;
struct item *item_b = b;
if (item_a->value < item_b->value)
return -1;
if (item_a->value > item_b->value)
return 1;
return 0;
}
// Your matrix:
struct item matrix[N][M];
/* Populate the matrix... make sure that each index is set,
* e.g. matrix[0][0] has index = 0.
*/
size_t i, j;
for (i = 0; i < M; i++) {
qsort(matrix[i], N, sizeof(struct item), compare_items);
/* Now the i-th row is sorted and you can take a look
* at the first k elements of the row.
*/
for (j = 0; j < k; j++) {
// Do something with matrix[i][j].index ...
}
}
I have written a function for FIR Filter which has an array as input and another array as output.This is my FIR Filter function here:
float * filter(float PATIENTSIGNAL[],float FILTERCOEF[])
I can use it without any problem, like the way hereunder:
float *FILTEROUT;
float FIROUT[8000];
FILTEROUT = filter(PATIENTSIGNAL, FILTERCOEF);
/* */
for (k = 0; k <= 1000; k++){
FIR[k] = 10 + FILTEROUT[k];
}
As you see I added number 10 to each element of my output array to evaluate that can I use this array for future computation,
But Here is my problem when I want use 2D array, This my function which return a 2D array correctly;
float(*Windowing(float SIGNAL[], int WINDOWSIZE));
I have used the Windowing function by this code in appropriate way:
patientwindow = Windowing(FILTEROUT, WINDOWSIZE);
and the all numbers in "patientwindow" array is correct but when I want to perform some simple operation like summation as here:
float evaluate[WINDOWSIZE][OVERLAP/4];
for (j = 0; j <= NUMBEROFWINDOWS; j++){
for (i = 0; i < WINDOWSIZE; i++){
evaluate[i][j] = 2+ (patientwindow[i][j]);
}
}
all elements of "evaluate" array are 0;
Would you please help me?
use
float** patientwindow;
float* is a pointer to array whereas float** is a pointer to matrix (for why is that the case see this answer https://stackoverflow.com/a/17953693/4996826 ).
If you want to use float* , then use following snippet of code:
evaluate[i][j] = 2 + (patientwindow[(i * NUMBEROFWINDOWS) + j]);
There is a pseudocode that I want to implement in C. But I am in doubt on how to implement a part of it. The psuedocode is:
for every pair of states qi, and qj, i<j, do
D[i,j] := 0
S[i,j] := notzero
end for
i and j, in qi and qj are subscripts.
how do I represent D[i,J] or S[i,j]. which data structure to use so that its simple and fast.
You can use something like
int length= 10;
int i =0, j= 0;
int res1[10][10] = {0, }; //index is based on "length" value
int res2[10][10] = {0, }; //index is based on "length" value
and then
for (i =0; i < length; i++)
{
for (j =0; j < length; j++)
{
res1[i][j] = 0;
res2[i][j] = 1;//notzero
}
}
Here D[i,j] and S[i,j] are represented by res1[10][10] and res2[10][10], respectively. These are called two-dimentional array.
I guess struct will be your friend here depending on what you actually want to work with.
Struct would be fine if, say, pair of states creates some kind of entity.
Otherwise You could use two-dimensional array.
After accept answer.
Depending on coding goals and platform, to get "simple and fast" using a pointer to pointer to a number may be faster then a 2-D array in C.
// 2-D array
double x[MAX_ROW][MAX_COL];
// Code computes the address in `x`, often involving a i*MAX_COL, if not in a loop.
// Slower when multiplication is expensive and random array access occurs.
x[i][j] = f();
// pointer to pointer of double
double **y = calloc(MAX_ROW, sizeof *y);
for (i=0; i<MAX_ROW; i++) y[i] = calloc(MAX_COL, sizeof *(y[i]));
// Code computes the address in `y` by a lookup of y[i]
y[i][j] = f();
Flexibility
The first data type is easy print(x), when the array size is fixed, but becomes challenging otherwise.
The 2nd data type is easy print(y, rows, columns), when the array size is variable and of course works well with fixed.
The 2nd data type also row swapping simply by swapping pointers.
So if code is using a fixed array size, use double x[MAX_ROW][MAX_COL], otherwise recommend double **y. YMMV
tI have the following code:
#define FIRST_COUNT 100
#define X_COUNT 250
#define Y_COUNT 310
#define z_COUNT 40
struct s_tsp {
short abc[FIRST_COUNT][X_COUNT][Y_COUNT][Z_COUNT];
};
struct s_tsp xyz;
I need to run through the data like this:
for (int i = 0; i < FIRST_COUNT; ++i)
for (int j = 0; j < X_COUNT; ++j)
for (int k = 0; k < Y_COUNT; ++k)
for (int n = 0; n < Z_COUNT; ++n)
doSomething(xyz, i, j, k, n);
I've tried to think of a more elegant, less brain-dead approach. ( I know that this sort of multidimensional array is inefficient in terms of cpu usage, but that is irrelevant in this case.) Is there a better approach to the way I've structured things here?
If you need a 4D array, then that's what you need. It's possible to 'flatten' it into a single dimensional malloc()ed 'array', however that is not quite as clean:
abc = malloc(sizeof(short)*FIRST_COUNT*X_COUNT*Y_COUNT*Z_COUNT);
Accesses are also more difficult:
*(abc + FIRST_COUNT*X_COUNT*Y_COUNT*i + FIRST_COUNT*X_COUNT*j + FIRST_COUNT*k + n)
So that's obviously a bit of a pain.
But you do have the advantage that if you need to simply iterate over every single element, you can do:
for (int i = 0; i < FIRST_COUNT*X_COUNT*Y_COUNT*Z_COUNT; i++) {
doWhateverWith *(abc+i);
}
Clearly this method is terribly ugly for most uses, and is a bit neater for one type of access. It's also a bit more memory-conservative and only requires one pointer-dereference rather than 4.
NOTE: The intention of the examples used in this post are just to explain the concepts. So the examples may be incomplete, may lack error handling, etc.
When it comes to usage of multi-dimension array in C, the following are the two possible ways.
Flattening of Arrays
In C, arrays are implemented as a contiguous memory block. This information can be used to manipulate the values stored in the array and allows rapid access to a particular array location.
For example,
int arr[10][10];
int *ptr = (int *)arr ;
ptr[11] = 10;
// this is equivalent to arr[1][0] = 10; assign a 2D array
// and manipulate now as a single dimensional array.
The technique of exploiting the contiguous nature of arrays is known as flattening of arrays.
Ragged Arrays
Now, consider the following example.
char **list;
list[0] = "United States of America";
list[1] = "India";
list[2] = "United Kingdom";
for(int i=0; i< 3 ;i++)
printf(" %d ",strlen(list[i]));
// prints 24 5 14
This type of implementation is known as ragged array, and is useful in places where the strings of variable size are used. Popular method is to have dynamic-memory-allocation to be done on the every dimension.
NOTE: The command line argument (char *argv[]) is passed only as ragged array.
Comparing flattened and ragged arrays
Now, lets consider the following code snippet which compares the flattened and ragged arrays.
/* Note: lacks error handling */
int flattened[30][20][10];
int ***ragged;
int i,j,numElements=0,numPointers=1;
ragged = (int ***) malloc(sizeof(int **) * 30);
numPointers += 30;
for( i=0; i<30; i++) {
ragged[i] = (int **)malloc(sizeof(int*) * 20);
numPointers += 20;
for(j=0; j<20; j++) {
ragged[i][j]=(int*)malloc(sizeof(int) * 10);
numElements += 10;
}
}
printf("Number of elements = %d",numElements);
printf("Number of pointers = %d",numPointers);
// it prints
// Number of elements = 6000
// Number of pointers = 631
From the above example, the ragged arrays require 631-pointers, in other words, 631 * sizeof(int *) extra memory locations for pointing 6000 integers. Whereas, the flattened array requires only one base pointer: i.e. the name of the array enough to point to the contiguous 6000 memory locations.
But OTOH, the ragged arrays are flexible. In cases where the exact number of memory locations required is not known you cannot have the luxury of allocating the memory for worst possible case. Again, in some cases the exact number of memory space required is known only at run-time. In such situations ragged arrays become handy.
Row-major and column-major of Arrays
C follows row-major ordering for multi-dimensional arrays. Flattening of arrays can be viewed as an effect due this aspect in C. The significance of row-major order of C is it fits to the natural way in which most of the accessing is made in the programming. For example, lets look at an example for traversing a N * M 2D matrix,
for(i=0; i<N; i++) {
for(j=0; j<M; j++)
printf(“%d ”, matrix[i][j]);
printf("\n");
}
Each row in the matrix is accessed one by one, by varying the column rapidly. The C array is arranged in memory in this natural way. On contrary, consider the following example,
for(i=0; i<M; i++) {
for(j=0; j<N; j++)
printf(“%d ”, matrix[j][i]);
printf("\n");
}
This changes the column index most frequently than the row index. And because of this there is a lot of difference in efficiency between these two code snippet. Yes, the first one is more efficient than the second one!
Because the first one accesses the array in the natural order (row-major order) of C, hence it is faster, whereas the second one takes more time to jump. The difference in performance would get widen as the number of dimensions and the size of element increases.
So when working with multi-dimension arrays in C, its good to consider the above details!
Say I have a 2D array of random boolean ones and zeroes called 'lattice', and I have a 1D array called 'list' which lists the addresses of all the zeroes in the 2D array. This is how the arrays are defined:
define n 100
bool lattice[n][n];
bool *list[n*n];
After filling the lattice with ones and zeroes, I store the addresses of the zeroes in list:
for(j = 0; j < n; j++)
{
for(i = 0; i < n; i++)
{
if(!lattice[i][j]) // if element = 0
{
list[site_num] = &lattice[i][j]; // store address of zero
site_num++;
}
}
}
How do I extract the x,y coordinates of each zero in the array? In other words, is there a way to return the indices of an array element through referring to its address?
EDIT: I need to make the code as efficient as possible, as I'm doing lots of other complicated stuff with much larger arrays. So a fast way of accomplishing this would be great
One solution is to map (x, y) to a natural number (say z).
z = N * x + y
x = z / N (integer division)
y = z % N
In this case, you should use int list[N * N];
Another solution is to just store the coordinates when you find a zero, something like:
list_x[site_num] = x;
list_y[site_num] = y;
site_num++;
Or you can define a struct of two ints.
Well, it is possible with some pointer arithmetic.
You have the address of your first element of lattice and the addresses of all zero-fields in list. You know the size of bool. By subtracting the first-elements address from a zero-field address and dividing by the size of bool you get a linar index. This linear index can be calculated into the 2-dim index by using modulo and division.
But why don't you store the 2-dim index within your list instead of the address? Do you need the addess or just the index?
And you should think about turning the for-loops around (outer loop i, inner loop j).
struct ListCoords
{
int x, y;
} coords[n*n];
for(i = 0; i < site_num; i++)
{
int index = list[i] - &lattice[0][0];
coords[i].x = index % n;
coords[i].y = index / n;
}
I may have the % and / operators backwards for your needs, but this should give you the idea.
How do I extract the x,y coordinates of each zero in the array? In other words, is there a way to return the indices of an array element through referring to its address?
You can't. Simple as that. If you need that information you need to pass it along with the arrays in question.
bool *list[n*n]; is an illegal statement in C89 (EDIT: Unless you made n a macro (yuck!)), you may wish to note that variable length arrays are a C99 feature.